Power allocation based on finite-horizon optimization for vehicle-to-roadside communications

In this paper, we study the power allocation strategy in a drive-thru scenario, where an access point (AP) is installed along the highway to provide Internet services to vehicles within its coverage range. We consider single-hop vehicle-to-roadside (V2R) communications for a vehicle that aims to upload data within the coverage range of the AP, where the bandwidth allocated to it is time-varying, and the size of the data is known upon it enters the area. The data bits received over a time slot are correctly received if the instantaneous channel capacity rt is greater than or equal to a threshold Rt, and corrupted otherwise. The vehicle has to pay an amount for data transmission according to the power consumption at each time slot whether the data bits are correctly received or not. The target is to complete the transmission of the traffic demand volume with the minimal cost. First, we consider the optimal power allocation strategy with a single AP and random vehicular traffic arrivals. We formulate it as a finite-horizon sequential power allocation problem. Then we solve the problem using dynamic programming and find the optimal power allocation strategy. The proof of the existing of the optimal value of the cost-to-go function is given after. Simulation results show that our proposed strategy achieves less cost than another heuristic strategy. The impacts of different traffic demand volumes, traffic densities, and outage probabilities on total cost are also analyzed.

[1]  Mustafa K. Mehmet Ali,et al.  A Performance Modeling of Connectivity in Vehicular Ad Hoc Networks , 2008, IEEE Transactions on Vehicular Technology.

[2]  B D Greenshields,et al.  A study of traffic capacity , 1935 .

[3]  Xu Guan,et al.  Robustness Evaluation of Decentralized Self-Information Dissemination Control Algorithms for VANET Tracking Applications , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[4]  Wing Cheong Lau,et al.  Modeling resource sharing for a road-side access point supporting drive-thru internet , 2009, VANET '09.

[5]  Joan García-Haro,et al.  Link-Layer Scheduling in Vehicle to Infrastructure Networks: An Optimal Control Approach , 2011, IEEE Journal on Selected Areas in Communications.

[6]  Y. Wu,et al.  Dynamic Rate Allocation, Routing and Spectrum Sharing for Multi-Hop Cognitive Radio Networks , 2009, 2009 IEEE International Conference on Communications Workshops.

[7]  Hannes Hartenstein,et al.  A tutorial survey on vehicular ad hoc networks , 2008, IEEE Communications Magazine.

[8]  Farid Ashtiani,et al.  A modified 802.11-based MAC scheme to assure fair access for vehicle-to-roadside communications , 2008, Comput. Commun..

[9]  Shuguang Cui,et al.  Power and Rate Control for Delay-Constrained Cognitive Radios Via Dynamic Programming , 2009, IEEE Transactions on Vehicular Technology.

[10]  Jing Zhao,et al.  On scheduling vehicle-roadside data access , 2007, VANET '07.

[11]  Hsiao-Hwa Chen,et al.  Quality-of-Service Driven Power and Sub-Carrier Allocation Policy for Vehicular Communication Networks , 2011, IEEE Journal on Selected Areas in Communications.

[12]  Jianping Pan,et al.  On the Uplink MAC Performance of a Drive-Thru Internet , 2012, IEEE Transactions on Vehicular Technology.

[13]  Vincent W. S. Wong,et al.  Dynamic Optimal Random Access for Vehicle-to-Roadside Communications , 2011, 2011 IEEE International Conference on Communications (ICC).

[14]  Ness B. Shroff,et al.  Finite-horizon energy allocation and routing scheme in rechargeable sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.